Strategic Data Science Lead for Mission-Critical Analytics

Prescient Edge; Florida; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive healthcare benefits

Retirement plan with no vesting

Tuition reimbursement

Job summary

Prescient Edge is seeking a Data Science Lead to support a federal government client. The role involves overseeing the development, deployment, and evaluation of predictive and prescriptive analytics to meet mission objectives and operational needs.

The position requires leadership, advanced ML expertise, and experience with Agile methodologies, data science and data engineering collaboration, and enterprise-scale analytics in cloud environments.

Qualifications

• Lead development of predictive and prescriptive analytics.
• Expert in ML techniques, modeling, and data provenance.
• Experience managing analytic sprints and Agile teams.
• Strong leadership and stakeholder engagement.
• Experience deploying analytics at enterprise scale.
• Familiar with cloud-based DS environments (AWS/Azure/Databricks).

Responsibilities

• Oversee development, deployment, and evaluation of analytics to align with mission objectives.
• Establish a framework distinguishing data science and data engineering tasks.
• Submit Predictive Analytics Strategy & Implementation Report detailing progress.
• Coordinate access to compute/storage for large-scale model training and analytics workloads.
• Fund compute/storage costs via inter-task chargeback arrangements with Government approval.

Skills

Advanced ML

Statistical modeling

Feature engineering

Agile

Leadership

Stakeholder mgmt

Education

Master's degree in DS/AI/CS

AWS/Azure certs

Tools

AWS

Azure

Databricks

Job description

Prescient Edge is seeking a Data Science Lead to support a federal government client. The role involves overseeing the development, deployment, and evaluation of predictive and prescriptive analytics to meet mission objectives and operational needs.

The position requires leadership, advanced ML expertise, and experience with Agile methodologies, data science and data engineering collaboration, and enterprise-scale analytics in cloud environments.